Zobrazeno 1 - 10
of 53
pro vyhledávání: '"Gataric, Milana"'
Autor:
Gatarić, Milana
In this thesis we study a novel approach to stable recovery of unknown compactly supported L2 functions from finitely many nonuniform samples of their Fourier transform, so-called Nonuniform Generalized Sampling (NUGS). This framework is based on a r
Externí odkaz:
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.683708
We propose a new method for high-dimensional semi-supervised learning problems based on the careful aggregation of the results of a low-dimensional procedure applied to many axis-aligned random projections of the data. Our primary goal is to identify
Externí odkaz:
http://arxiv.org/abs/2304.09154
High-resolution signal recovery via generalized sampling and functional principal component analysis
Autor:
Gataric, Milana
In this paper, we introduce a computational framework for recovering a high-resolution approximation of an unknown function from its low-resolution indirect measurements as well as high-resolution training observations by merging the frameworks of ge
Externí odkaz:
http://arxiv.org/abs/2002.08724
Autor:
Gordon, George S. D., Gataric, Milana, Ramos, Alberto Gil C. P., Mouthaan, Ralf, Williams, Calum, Yoon, Jonghee, Wilkinson, Timothy D., Bohndiek, Sarah E.
Publikováno v:
Phys. Rev. X 9, 041050 (2019)
The ability to form images through hair-thin optical fibres promises to open up new applications from biomedical imaging to industrial inspection. Unfortunately, deployment has been limited because small changes in mechanical deformation (e.g. bendin
Externí odkaz:
http://arxiv.org/abs/1904.02644
Autor:
Gataric, Milana, Gordon, George S. D., Renna, Francesco, Ramos, Alberto Gil C. P., Alcolea, Maria P., Bohndiek, Sarah E.
We introduce a framework for the reconstruction of the amplitude, phase and polarisation of an optical vector-field using calibration measurements acquired by an imaging device with an unknown linear transformation. By incorporating effective regular
Externí odkaz:
http://arxiv.org/abs/1804.10636
We introduce a new method for sparse principal component analysis, based on the aggregation of eigenvector information from carefully-selected axis-aligned random projections of the sample covariance matrix. Unlike most alternative approaches, our al
Externí odkaz:
http://arxiv.org/abs/1712.05630
Akademický článek
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Publikováno v:
Applied and Computational Harmonic Analysis, 46(2): 226-249, 2019
We study the problem of recovering an unknown compactly-supported multivariate function from samples of its Fourier transform that are acquired nonuniformly, i.e. not necessarily on a uniform Cartesian grid. Reconstruction problems of this kind arise
Externí odkaz:
http://arxiv.org/abs/1606.07698
Autor:
Gataric, Milana, Poon, Clarice
In a series of recent papers (Adcock, Hansen and Poon, 2013, Appl. Comput. Harm. Anal. 45(5):3132-3167), (Adcock, Gataric and Hansen, 2014, SIAM J. Imaging Sci. 7(3):1690-1723) and (Adcock, Hansen, Kutyniok and Ma, 2015, SIAM J. Math. Anal. 47(2):119
Externí odkaz:
http://arxiv.org/abs/1505.05308
We provide sufficient density condition for a set of nonuniform samples to give rise to a set of sampling for multivariate bandlimited functions when the measurements consist of pointwise evaluations of a function and its first $k$ derivatives. Along
Externí odkaz:
http://arxiv.org/abs/1411.0300